Event Sequence Generation from Aviation Accident Reports

Xinyu Zhao, Hao Yan, Yongming Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the aviation domain, historical aviation accidents are recorded to prevent catastrophe in the future. The national transportation safety board (NTSB) provides a large volume of accident reports and designs aviation event taxonomy to summarize what happens during the accidents. By utilizing the event taxonomy, we are able to design tools to analyze the accident reports, such as information retrieval systems, fault tree analysis, and causal chain analysis. However, one of the challenges is how to appropriately identify the accident reports with those event taxonomies. Traditionally, domain experts will label those events manually, which is time-consuming and subjective. In this paper, we propose the formulate the event labeling task as a sequence generation task. By adopting an advanced sequence generation framework, our experiment results show that we can achieve promising results on those frequent events.

Original languageEnglish (US)
Title of host publicationAIAA AVIATION 2022 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624106354
DOIs
StatePublished - 2022
EventAIAA AVIATION 2022 Forum - Chicago, United States
Duration: Jun 27 2022Jul 1 2022

Publication series

NameAIAA AVIATION 2022 Forum

Conference

ConferenceAIAA AVIATION 2022 Forum
Country/TerritoryUnited States
CityChicago
Period6/27/227/1/22

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Aerospace Engineering

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